Sensor Calibration Method and Apparatus

ABSTRACT

A sensor calibration method and apparatus are provided Location information of a target detected by the radar ( 110 ) is matched against map information to determine a calibration value of the radar ( 110 ), and then location information of a pixel of a target corresponding to the camera ( 120 ) in a global coordinate system is determined based on calibrated radar measurement data, so as to further determine a calibration value of the camera ( 120 ). In this way, for the roadside sensing system ( 200 ) that includes the single radar ( 110 ) and the single camera ( 120 ), manual field calibration is no longer required, which can effectively improve calibration efficiency of sensors in the roadside sensing system ( 200 ). This method improves an advanced driving assistance system ADAS capability of a terminal in automatic driving or assisted driving, and may be applied to a vehicle network, for example, V2X, LTE-V, and V2V.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of International Application No.PCT/CN2020/116143, filed on Sep. 18, 2020, which claims priority toChinese Patent Application No. 201910913472.9, filed on Sep. 25, 2019.The disclosures of the aforementioned applications are herebyincorporated by reference in their entireties.

TECHNICAL FIELD

This application relates to the field of automatic driving technologies,and in particular, to a sensor space calibration method and apparatus.

BACKGROUND

With development of society, intelligent vehicles are gradually enteringpeople's daily life. Sensors play a quite important role in assisteddriving and automatic driving of the intelligent vehicles. A roadsidemonitoring system can effectively monitor targets in a front coveragearea by using active sensors such as a distance sensor and an imagesensor. Using multi-sensor fusion is a development trend. It greatlyimproves an environment sensing capability of a roadside sensingstation. With reference to a vehicle to everything (vehicle toeverything, V2X) technology, overall road safety performance can beimproved. The fusion of the distance sensor and the image sensor cangive play to advantages of the two sensors, and has obvious advantagesin terms of obtaining environment information and performing targetidentification.

In data fusion processing of a multi-sensor detection system, a unifiedcoordinate system needs to be provided, so as to ensure that dataobtained by a plurality of sensors can have a unified referencestandard, so that the data of the plurality of sensors can be convertedto each other. Therefore, the distance sensor and the image sensorshould be spatially self-calibrated before the two sensors are used fordata fusion processing. Currently, a multi-radar and/or multi-camerajoint calibration processing manner is mainly used in calibrationsolutions for a camera and a millimeter wave radar. However, currently,for a calibration solution for a single-radar and single-camera sensingsystem, extra camera assistance or manual field calibration need to beused, and efficiency is relatively low.

Therefore, it is urgently necessary to provide a calibration solutionfor a single-radar and single-camera sensing system to resolve a problemthat calibration efficiency of the single-radar and single-camerasensing system is relatively low.

SUMMARY

This application provides a sensor calibration method and apparatus,which can improve calibration efficiency of a single-radar andsingle-camera sensing system.

According to a first aspect, a sensor calibration method is provided. Inan example, the method may be applied to a roadside sensing system, andthe roadside sensing system includes a single-radar sensor, a camera,and a fusion processing module. The radar and the camera are disposed ona roadside, and the fusion processing module may be disposed on aroadside or in the cloud. The method may be executed by the fusionprocessing module. In an example, the camera in this embodiment of thisapplication is a monocular camera.

In this method, first radar measurement data of a first target may beobtained first, and a calibration value of the radar sensor isdetermined based on map information and the first radar measurementdata. Then, first radar calibration measurement data of a second targetmay be determined based on second radar measurement data of the secondtarget and the calibration value of the radar sensor. Then, first camerameasurement data of the second target is obtained, and a calibrationvalue of a camera sensor is determined based on the first radarcalibration measurement data and the first camera measurement data.

Therefore, in this embodiment of this application, location informationof a target detected by the radar is matched against the map informationto determine the calibration value of the radar sensor, and thenlocation information of a pixel of a target corresponding to the camerain the global coordinate system may be determined based on calibratedradar measurement data, that is, radar calibration measurement data, soas to further determine the calibration value of the camera sensor.Therefore, according to the sensor space calibration solution providedin the embodiment of this application, for a sensing system thatincludes a single radar and a monocular camera, manual field calibrationis no longer required, which can effectively improve calibrationefficiency of sensors in the sensing system.

With reference to the first aspect, in some implementations of the firstaspect, a fitting straight line track of the first target may bedetermined based on the foregoing first radar measurement data, and thena first slope of the fitting straight line track of the first target isdetermined. Then, a second slope of a first road reference target in aworld coordinate system may be determined based on the map information,where the first road reference target is corresponding to the fittingstraight line track of the first target. Then, the calibration value ofthe radar sensor may be determined based on the first slope and thesecond slope.

Herein, when the first target is a stationary point target, the firstradar measurement data may be location information of a plurality offirst targets. When the first target is a moving target, the first radarmeasurement data may be location information of a plurality of movingpositions of the first target.

In this embodiment of this application, the first slope is a slope ofthe fitting straight line track of the first target in a localcoordinate system of the radar, and the second slope is a slope of theroad reference target in a global coordinate system. In an example, whenthe map information is a GPS map, the global coordinate system may bethe world coordinate system.

In an example, an AOA of the first target in the local coordinate systemof the radar may be determined based on the first slope. The AOA may berepresented as θ_(r). An AOA of the first target in the world coordinatesystem is determined based on the second slope. For example, the AOA maybe represented as θ_(l). In this case, the calibration value Δθ of theradar sensor may be represented as: Δθ=θ_(l)−θ_(r).

Therefore, in this embodiment of this application, the first slope ofthe fitting straight line track of the first target is obtained, thesecond slope of the first road, in the world reference system,corresponding to the fitting straight line track of the first target isobtained, and the calibration value of the radar sensor is determinedbased on the first slope and the second slope. Therefore, according tothe sensor space calibration solution provided in the embodiment of thisapplication, for a sensing system that includes a single radar and amonocular camera, manual field calibration is no longer required, whichcan effectively improve calibration efficiency of sensors in the sensingsystem.

With reference to the first aspect, in some implementations of the firstaspect, k first radar measurement values corresponding to k firsttargets may be obtained. The k first targets are corresponding to afirst road reference target in the map information, and k is an integergreater than or equal to 2. Then, k fitting straight line trackscorresponding to the k first targets are determined based on n firstradar measurement values corresponding to the k first targets, and anaverage value of k first slopes corresponding to the k fitting straightline tracks is determined.

Then, a second slope of the first road reference target in the worldcoordinate system may be determined based on the map information. Then,the calibration value of the radar sensor may be determined based on theaverage value of the k first slopes and the second slope.

In an example, an AOA of the first target in the local coordinate systemof the radar may be determined based on the average value of the k firstslopes. The AOA may be represented as {tilde over (θ)}_(r). An AOA ofthe first target in the world coordinate system is determined based onthe second slope. For example, the AOA may be represented as θ_(l). Inthis case, the calibration value Δθ of the radar sensor may berepresented as: Δθ=θ_(l)−{acute over (θ)}_(r).

Therefore, in this embodiment of this application, the average value ofthe plurality of first slopes is determined after location informationof the first target is measured for a plurality of times, and thecalibration value of the radar sensor is determined based on the averagevalue of the first slopes, thereby improving precision of thecalibration value of the radar sensor.

With reference to the first aspect, in some implementations of the firstaspect, location information of the second target in the worldcoordinate system may be determined based on the first radar calibrationmeasurement data. Then, the calibration value of the camera sensor isdetermined based on the first camera measurement data and the locationinformation of the second target in the world coordinate system. In anexample, calibration point coordinates in the global coordinate systemthat are corresponding to a pixel of the second target in the localcoordinate system of the camera are the location information of thesecond target in the world coordinate system.

In an example, the first radar calibration measurement data may be anAOA that is of the second target in the global coordinate system andobtained through calibration performed on an AOA measured by the radar.For example, when the AOA of the second target in the local coordinatesystem of the radar that is measured by the radar is {circumflex over(φ)}, the first radar calibration measurement data of the second targetmay be ({circumflex over (φ)}+Δθ).

In some possible implementations, for a second target that appears atdifferent moments in a same location in images obtained by the camera,location information that is of the second target appearing at thedifferent moments and observed by the radar may be determined, and anaverage value of the plurality of pieces of location information isdetermined. Then, first radar calibration measurement data of the secondtarget is determined based on the average value of the plurality ofpieces of location information. Herein, the location information islocation information of the second target in the local coordinate systemof the radar. In an example, the location information may include, forexample, a distance and an AOA.

It should be noted that, because the plurality of second targets aretargets that appear at different moments in the same location obtainedby the camera, camera measurement data corresponding to the plurality ofsecond targets is the same.

Therefore, in this embodiment of this application, location informationof the second target is measured for a plurality of times, and theaverage value of the location information of the plurality of secondtargets is determined. Then, first radar calibration measurement data ofthe second targets is determined based on the average value of thelocation information of the plurality of second targets. This canimprove precision of radar calibration measurement data.

With reference to the first aspect, in some implementations of the firstaspect, a plurality of pieces of first radar calibration measurementdata corresponding to the second target that appears at the differentmoments in the same location in the images obtained by the camera may befurther obtained. Then, a plurality of pieces of location information ofthe plurality of second targets in the world coordinate system may bedetermined based on the plurality of pieces of first radar calibrationmeasurement data, and an average value of the plurality of pieces oflocation information may be determined. Then, the calibration value ofthe camera sensor may be determined based on the average value of theplurality of pieces of location information and first camera measurementdata corresponding to the plurality of second targets.

For example, h pieces of first radar calibration measurement datacorresponding to h second targets and h pieces of first camerameasurement data of the h second targets may be obtained. The firstcamera measurement data of the h second targets is the same, and h is aninteger greater than or equal to 2.

Then, h pieces of location information of the h second targets in theworld coordinate system are determined based on the h pieces of firstradar calibration measurement data of the h second targets, and anaverage value of the h pieces of location information of the h secondtargets is determined.

Then, the calibration value of the camera sensor is determined based onthe average value of the h pieces of location information of the hsecond targets and the h pieces of first camera measurement data of theh second targets.

Therefore, in this embodiment of this application, location informationof the second target is measured for a plurality of times, a pluralityof pieces of location information in the world coordinate system thatare corresponding to the location information of the plurality of secondtargets are determined, and then an average value of the plurality ofpieces of location information of the plurality of second targets in theworld coordinate system is determined. Then, the calibration value ofthe camera sensor is determined based on the average value. This canimprove precision of the calibration value of the camera sensor.

With reference to the first aspect, in some implementations of the firstaspect, travelling data of the foregoing first target collected by thecamera sensor may be obtained, and then radar measurement data collectedby the radar sensor is searched for first radar measurement data thatmatches the travelling data.

In this way, the first radar measurement data corresponding to themoving target may be obtained, and then the calibration value of theradar sensor may be determined based on the map information and thefirst radar measurement data corresponding to the moving target.

In some possible implementations, the first target and the second targetmay be same objects, but implementation of this application is notlimited thereto.

In this embodiment of this application, after determining thecalibration value of the radar sensor, the fusion processing module maysend the calibration value of the radar sensor to the radar. Afterdetermining the calibration value of the camera sensor, the fusionprocessing module may send the calibration value of the camera sensor tothe camera.

According to a second aspect, a sensor calibration method is provided.In an example, the method may be applied to a roadside sensing system,and the roadside sensing system includes a single-radar sensor, acamera, and a fusion processing module. The radar and the camera aredisposed on a roadside, and the fusion processing module may be disposedon a roadside or in the cloud. The method may be performed by thecamera. In an example, the camera in this embodiment of this applicationis a monocular camera.

In this method, a calibration value of a camera sensor sent by thefusion processing module may be received, where the calibration value ofthe camera sensor is obtained based on first radar calibrationmeasurement data of a second target and first camera measurement data ofthe second target, and the first radar calibration measurement data isobtained based on second radar measurement data of the second target anda calibration value of the radar sensor. Then, a measurement parameterof the camera sensor may be calibrated based on the calibration value ofthe camera sensor.

Therefore, in this embodiment of this application, the camera mayreceive the calibration value of the camera sensor sent by the fusionprocessing module, and then may calibrate the measurement parameter ofthe camera sensor based on the calibration value of the camera sensor.Therefore, according to the sensor space calibration solution providedin the embodiment of this application, for a sensing system thatincludes a single radar and a monocular camera, manual field calibrationis no longer required, which can effectively improve calibrationefficiency of sensors in the sensing system.

With reference to the second aspect, in some implementations of thesecond aspect, camera measurement data of a plurality of targets may befurther obtained, and a first target that meets a preset reportingcondition is determined in the plurality of targets based on the camerameasurement data. Then, travelling data of the first target is obtained,and the travelling data of the first target is sent to the fusionprocessing module. The travelling data is used to indicate the fusionmodule to search radar measurement data collected by the radar sensorfor first radar measurement data that is of the first target and matchesthe travelling data.

In an example, the preset reporting condition is that vehicles in ascene picture photographed by the camera are sparse, for example, onlyone vehicle exists. In this case, the vehicle may be used as the firsttarget.

According to a third aspect, a sensor calibration method is provided. Inan example, the method may be applied to a roadside sensing system, andthe roadside sensing system includes a single-radar sensor, a camera,and a fusion processing module. The radar and the camera are disposed ona roadside, and the fusion processing module may be disposed on aroadside or in the cloud. The method may be performed by the radar. Inan example, the camera in this embodiment of this application is amonocular camera.

In this method, a calibration value of the radar sensor sent by thefusion processing module may be received, and the calibration value ofthe radar sensor is obtained based on first radar measurement data of afirst target and map data. Then, a measurement parameter of the radarsensor is calibrated based on the calibration value of the radar sensor.

Therefore, in this embodiment of this application, the radar may receivethe calibration value of the radar sensor sent by the fusion processingmodule, and then may calibrate the measurement parameter of the radarsensor based on the calibration value of the radar sensor. Therefore,according to the sensor space calibration solution provided in theembodiment of this application, for a sensing system that includes asingle radar and a monocular camera, manual field calibration is nolonger required, which can effectively improve calibration efficiency ofsensors in the sensing system.

According to a fourth aspect, an embodiment of this application providesa sensor calibration apparatus, configured to perform the method in anyone of the first aspect or the possible implementations of the firstaspect. Specifically, the apparatus includes a module configured toperform the method in any one of the first aspect or the possibleimplementations of the first aspect. The apparatus includes an obtainingunit and a determining unit.

The obtaining unit is configured to obtain first radar measurement dataof a first target.

The determining unit is configured to determine a calibration value of aradar sensor based on map information and the first radar measurementdata.

The determining unit is further configured to determine first radarcalibration measurement data of a second target, where the first radarcalibration measurement data is obtained based on second radarmeasurement data of the second target and the calibration value of theradar sensor.

The obtaining unit is further configured to obtain first camerameasurement data of the second target.

The determining unit is further configured to determine a calibrationvalue of a camera sensor based on the first radar calibrationmeasurement data and the first camera measurement data.

With reference to the fourth aspect, in some implementations of thefourth aspect, the determining unit is specifically configured to:determine a fitting straight line track of the first target based on thefirst radar measurement data, and determine a first slope of the fittingstraight line track of the first target. Then, a second slope of a firstroad reference target in a world coordinate system is determined basedon the map information, where the first road reference target iscorresponding to the fitting straight line track of the first target.Then, the calibration value of the radar sensor is determined based onthe first slope and the second slope.

With reference to the fourth aspect, in some implementations of thefourth aspect, the determining unit is specifically configured to obtaink first radar measurement values corresponding to k first targets. The kfirst targets are corresponding to the first road reference target inthe map information, and k is an integer greater than or equal to 2.Then, k fitting straight line tracks corresponding to the k firsttargets are determined based on n first radar measurement valuescorresponding to the k first targets. Then, an average value of k firstslopes corresponding to the k fitting straight line tracks isdetermined. Then, a second slope of the first road reference target in aworld coordinate system is determined based on the map information.Then, the calibration value of the radar sensor is determined based onthe average value of the k first slopes and the second slope.

With reference to the fourth aspect, in some implementations of thefourth aspect, the determining unit is specifically configured todetermine location information of the second target in the worldcoordinate system based on the first radar calibration measurement data.Then, the calibration value of the camera sensor is determined based onthe first camera measurement data and the location information of thesecond target in the world coordinate system.

With reference to the fourth aspect, in some implementations of thefourth aspect, the determining unit is specifically configured to obtainh pieces of first radar calibration measurement data corresponding to hsecond targets and h pieces of first camera measurement data of the hsecond targets, where the first camera measurement data of the h secondtargets is the same, and h is an integer greater than or equal to 2.Then, h pieces of location information of the h second targets in theworld coordinate system are determined based on the h pieces of firstradar calibration measurement data of the h second targets. Then, anaverage value of the h pieces of location information of the h secondtargets is determined. Then, the calibration value of the camera sensoris determined based on the average value of the h pieces of locationinformation of the h second targets and the h pieces of first camerameasurement data of the h second targets.

With reference to the fourth aspect, in some implementations of thefourth aspect, the obtaining unit is specifically configured to: obtaintravelling data of the first target collected by the camera sensor; andsearch radar measurement data collected by the radar sensor for thefirst radar measurement data that matches the travelling data.

According to a fifth aspect, an embodiment of this application providesa sensor calibration apparatus, configured to perform the method in anyone of the second aspect or the possible implementations of the secondaspect. Specifically, the apparatus includes a module configured toperform the method in any one of the second aspect or the possibleimplementations of the second aspect. The apparatus includes a receivingunit and a processing unit.

The receiving unit is configured to receive a calibration value of acamera sensor sent by a fusion processing module, where the calibrationvalue of the camera sensor is obtained based on first radar calibrationmeasurement data of a second target and first camera measurement data ofthe second target, and the first radar calibration measurement data isobtained based on second radar measurement data of the second target anda calibration value of the radar sensor.

The processing unit is configured to calibrate a measurement parameterof the camera sensor based on the calibration value of the camerasensor.

With reference to the fifth aspect, in some possible implementations ofthe fifth aspect, the apparatus further includes an obtaining unit,configured to obtain camera measurement data of a plurality of targets.Then, the processing unit is further configured to determine, from theplurality of targets based on the camera measurement data of theplurality of targets that is obtained by the obtaining unit, a firsttarget that meets a preset reporting condition.

The obtaining unit is further configured to obtain travelling data ofthe first target.

The apparatus further includes a sending unit, configured to send thetravelling data of the first target to the fusion processing module,where the travelling data is used to indicate the fusion module tosearch radar measurement data collected by the radar sensor for firstradar measurement data that is of the first target and matches thetravelling data.

According to a sixth aspect, an embodiment of this application providesa sensor calibration apparatus, configured to perform the method in anyone of the third aspect or the possible implementations of the thirdaspect. Specifically, the apparatus includes a module configured toperform the method in any one of the third aspect or the possibleimplementations of the second aspect. The apparatus includes a receivingunit and a processing unit.

The receiving unit is configured to receive a calibration value of aradar sensor sent by a fusion processing module, where the calibrationvalue of the radar sensor is obtained based on first radar measurementdata of a first target and map data.

The processing unit is configured to calibrate a measurement parameterof the radar sensor based on the calibration value of the radar sensor.

According to a seventh aspect, an embodiment of this applicationprovides a sensor calibration apparatus, including a memory and aprocessor. The memory is configured to store instructions. The processoris configured to execute the instructions stored in the memory. When theprocessor executes the instructions stored in the memory, the executionenables the processor to perform the method in any one of the firstaspect or the possible implementations of the first aspect.

According to an eighth aspect, an embodiment of this applicationprovides a sensor calibration apparatus, including a memory and aprocessor. The memory is configured to store instructions. The processoris configured to execute the instructions stored in the memory. When theprocessor executes the instructions stored in the memory, the executionenables the processor to perform the method in any one of the secondaspect or the possible implementations of the second aspect.

According to a ninth aspect, an embodiment of this application providesa sensor calibration apparatus, including a memory and a processor. Thememory is configured to store instructions. The processor is configuredto execute the instructions stored in the memory. When the processorexecutes the instructions stored in the memory, the execution enablesthe processor to perform the method in any one of the third aspect orthe possible implementations of the third aspect.

According to a tenth aspect, an embodiment of this application providesa computer-readable medium, configured to store a computer program. Thecomputer program includes instructions used to perform the method in anyone of the first aspect or the possible implementations of the firstaspect, or instructions used to perform the method in any one of thesecond aspect or the possible implementations of the second aspect, orinstructions used to perform the method in any one of the third aspector the possible implementations of the third aspect.

According to an eleventh aspect, a computer program product is provided.The computer program product includes instructions. When theinstructions are run on a computer, the computer is enabled to implementthe method in any one of the first aspect and the possibleimplementations of the first aspect, the method in any one of the secondaspect and the possible implementations of the second aspect, or themethod in any one of the third aspect and the possible implementationsof the third aspect.

According to a twelfth aspect, a sensor calibration system is provided,including the sensor calibration apparatus in the fourth aspect, thesensor calibration apparatus in the fifth aspect, and the sensorcalibration apparatus in the sixth aspect.

According to a thirteenth aspect, a sensor calibration system isprovided, including the sensor calibration apparatus in the seventhaspect, the sensor calibration apparatus in the eighth aspect, and thesensor calibration apparatus in the ninth aspect.

According to a fourteenth aspect, a chip is provided, including aprocessor and a communications interface. The processor is configured toinvoke instructions from the communications interface and run theinstructions. When the processor executes the instructions, the methodin any one of the first aspect to the third aspect or the possibleimplementations of the first aspect to the third aspect is implemented.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a schematic diagram of location conversion of a plurality ofsensors;

FIG. 2 is a schematic diagram of an application scenario applicable toan embodiment of this application;

FIG. 3 is a schematic diagram of a sensing system according to anembodiment of this application;

FIG. 4 is a schematic flowchart of a sensor calibration method accordingto an embodiment of this application;

FIG. 5 is a schematic flowchart of another sensor calibration methodaccording to an embodiment of this application;

FIG. 6 is a schematic flowchart of another sensor calibration methodaccording to an embodiment of this application;

FIG. 7 is a schematic block diagram of a sensor calibration apparatusaccording to an embodiment of this application;

FIG. 8 is a schematic block diagram of another sensor calibrationapparatus according to an embodiment of this application;

FIG. 9 is a schematic block diagram of another sensor calibrationapparatus according to an embodiment of this application; and

FIG. 10 is a schematic block diagram of another sensor calibrationapparatus according to an embodiment of this application.

DESCRIPTION OF EMBODIMENTS

The following describes the technical solutions in this application withreference to the accompanying drawings.

First, a process of converting locations of a plurality of sensors to aunified coordinate system is described with reference to FIG. 1. In anexample, the plurality of sensors include, for example, a radar 110 anda camera 120. As shown in FIG. 1, the unified coordinate system is, forexample, a global coordinate system O_(W)-X_(W)Y_(W)Z_(W). Using atarget P as an example, the radar 110 may obtain location data of thetarget P in a local coordinate system (O_(R)-X_(R)Y_(R)) of the radar.The location data includes a distance (O_(R)P) between the target P andthe radar and an angle of arrival (angle of arrival, AOA). Based on acalibration parameter of the radar 110, coordinate system conversion maybe performed on the location data of the target P, that is, the target Pis projected from the local coordinate system O_(R)-X_(R)Y_(R) to theglobal coordinate system O_(W)-X_(W)Y_(W)Z_(W), to obtain location dataof the target P in the global coordinate system.

In an example, the calibration parameter of the radar 110 is, forexample, a radar beam azimuth and/or radar location coordinates.

Continuing to use the target P as an example, the camera 120 can obtainpixel coordinates of the target P in a pixel coordinate system O-XY. Ina process of converting the pixel coordinates of the target P to theglobal coordinate system O_(W)-X_(W)Y_(W)Z_(W), the target P needs to befirst converted from the pixel coordinate system O-XY to a localcoordinate system O_(C)-X_(C)Y_(C)Z_(C) of the camera 120, and thenconverted from the local coordinate system O_(C)-X_(C)Y_(C)Z_(C) of thecamera 120 to the global coordinate system O_(W)-X_(W)Y_(W)Z_(W).Because the camera 120 cannot obtain distance information of the targetP, in a coordinate system conversion process, a location of a pixel inthe global coordinate system needs to be spatially calibrated.

In an example, a calibration parameter of the camera 120 is, forexample, a conversion relationship between a location of a target in thelocal coordinate system of the camera 120 and a location of the targetin the global coordinate system. For example, the conversionrelationship may be specifically represented as a space conversionmatrix. In some possible implementations, in a process of determiningthe calibration parameter of the camera 120, a location of a target inthe local coordinate system of the camera and location coordinates ofthe target in the global coordinate system may be first obtained.

In some possible implementations, the global coordinate system may be aworld coordinate system or an earth coordinate system. In this case, thelocation coordinates of the target in the global coordinate system mayalso be described as an actual location of the target.

For example, for a distance sensor such as a millimeter wave radar or alaser radar, calibration may be performed on each radar azimuth by usinga distributed multi-radar joint calibration method. For another example,for an image sensor such as a camera, a binocular camera is mainly usedto obtain spatial location information of a target by using a visualangle difference, so as to complete calibration of the binocular camera.However, currently, manual field calibration is mainly used for a singleradar and a single camera, and efficiency is relatively low.

Based on this, an embodiment of this application provides a sensor spacecalibration solution, so that for a sensing system that includes asingle radar and a monocular camera, manual field calibration is nolonger required, which can effectively improve calibration efficiency ofsensors in the sensing system.

FIG. 2 is a schematic diagram of an application scenario applicable toan embodiment of this application. As shown in FIG. 2, the sensingsystem 200 may be disposed on a roadside, and may be configured toobtain roadside environment information, perform target identification,perform effective monitoring on a target in a coverage area, and thelike. This is not limited in the embodiments of this application. Forexample, the environment information is at least one of a lane line, aroadside line, a zebra crossing, a sign indicator, a pedestrian, avehicle, a railing, and a street lamp. The target is, for example, atleast one object in the environment information. It should be noted thatFIG. 2 shows only some environmental information by way of example, butthe embodiments of this application are not limited to the scope shownin FIG. 2.

As shown in FIG. 2, the sensing system 200 may include a radar 110 and acamera 120, where the camera 120 may be a monocular camera. In addition,in this embodiment of this application, there may be one radar 110 inthe sensing system 200, and there may be one camera 120.

A sensing area of the radar 110 may be, for example, an area that can bedetected by the radar 110. In an example, the sensing area may be anarea included in the dashed line 101 in FIG. 2 (which may also bereferred to as an area 101). A sensing area of the camera 120 may be,for example, an area that can be photographed by the camera 120. In anexample, the sensing area may be an area included in the dashed line 102in FIG. 2 (which may also be referred to as an area 102). In thisembodiment of this application, areas covered by a radar and a camera ina same sensing station have an overlapping part, for example, a shadowarea 103 in FIG. 2.

In this embodiment of this application, the sensing system 200 furtherincludes a data fusion module. The radar 110 and the camera 120 may sendcollected data to the data fusion module in real time, and the datafusion module processes the received data to obtain a calibrationparameter of the radar 110 and a calibration parameter of the camera120. Herein, the calibration parameter of the radar 110 may also bereferred to as a calibration value of a radar sensor, and thecalibration parameter of the camera 120 may also be referred to as acalibration value of a camera sensor. However, the embodiments of thisapplication are not limited thereto.

In some possible descriptions, the fusion processing module may also bereferred to as a data fusion center, a calibration solving module, orthe like. This is not limited in the embodiments of this application.

It should be noted that, in this embodiment of this application,measurement data in the area 103 of the radar 110 and the camera 120 maybe calibrated.

In some possible implementations, the data fusion center may be locatedon a roadside, for example, integrated with the sensing station 200. Insome possible implementations, the data fusion center may alternativelybe disposed in the cloud. This is not limited in this embodiment of thisapplication.

FIG. 3 is a schematic diagram of a sensing system 200 according to anembodiment of this application. As shown in FIG. 3, the sensing system200 may include a detection module 210 and a fusion processing module220. The detection module 210 includes a millimeter wave radar and amonocular camera. Herein, the millimeter wave radar may be used as anexample of the foregoing radar 110, and the monocular camera may be usedas an example of the foregoing camera 120. For example, in some possibleembodiments, the radar may alternatively be a laser radar.

In some possible implementations, the detection module 210 may be usedfor target detection, lane line detection, roadside detection, and thelike. In an example, the monocular camera and the radar each mayidentify a target in a respective sensing area and obtain locationinformation and other related information of the target. The monocularcamera may obtain a real-time image of a road in the sensing area of themonocular camera, so as to identify left and right lane lines and thelike of a lane in the image. The millimeter wave radar may identifyobstacles in its sensing area, such as static obstacles that arecontinuous and regular such as a fence on each side of a road, to obtaininformation about a road edge (that is, a roadside line).

In a specific example, the monocular camera may identify a target ofinterest in the obtained image, and output information such as a lane inwhich the target is located or a driving direction to the fusionprocessing module 220. The millimeter wave radar may output a relativelocation or a track of the target (or another object) to the fusionprocessing module 220. Inputs of the fusion processing module 220include detection information output by the millimeter wave radar andthe monocular camera, and map information. The fusion processing module220 fuses the input data to determine calibration parameters of themillimeter wave radar and the monocular camera. Then, the fusionprocessing module 220 may output the calibration parameter of themillimeter wave radar to the millimeter wave radar, and output thecalibration parameter of the monocular camera to the monocular camera.

In an example, the map information may be current road informationretrieved from a global positioning system (global positioning system,GPS) offline map database, or current road information in a GPS onlinemap. Herein, the road information is, for example, longitude andlatitude of a lane. This is not limited in the embodiments of thisapplication.

Therefore, in this embodiment of this application, the fusion processingmodule 220 can determine the calibration parameters of the millimeterwave radar and the monocular camera based on the map information and thedetection information that is output by the millimeter wave radar andthe monocular camera. Therefore, according to the sensor spacecalibration solution provided in the embodiment of this application, fora sensing system that includes a single radar and a monocular camera,manual field calibration is no longer required, which can effectivelyimprove calibration efficiency of sensors in the sensing system.

FIG. 4 is a schematic flowchart of a sensor calibration method 400according to an embodiment of this application. In an example, themethod may be performed by the foregoing fusion processing module 220.The method includes steps 410 to 450.

410: Obtain first radar measurement data of a first target.

In a possible implementation, the first radar measurement data for thefirst target that is output by a radar may be obtained. Herein, thefirst target may be a roadside obstacle, and the first radar measurementdata may be coordinates of the obstacle. For example, the first targetmay be a plurality of stationary point targets such as roadside fences,and the first radar measurement data is coordinates [x_(r)(i),y_(r)(i)]of the plurality of stationary point targets. Herein, i represents anumber of a stationary point. Herein, the first radar measurement datacan represent information about a road edge (that is, a roadside line).

In another possible implementation, travelling data of the first targetthat is collected by a camera and radar measurement data that iscollected by the radar may be first obtained, then radar measurementdata that matches the travelling data of the first target is searchedfor in the radar measurement data collected by the radar, and the radarmeasurement data is used as the foregoing first radar measurement data.

In an example, a scene picture photographed by the camera may beobtained, and a target vehicle (an example of the first target) andtravelling data of the target vehicle are obtained from the scenepicture. For example, a quantity of vehicles in a scenario and a drivingdirection may be determined. When it is determined that the vehicles inthe scenario are sparse (for example, there is only one vehicle in thescenario), one of the vehicles may be used as the target vehicle. Afterthe target vehicle travels a distance along a lane, the camera mayreport driving data such as a driving direction, the driving lane, and adriving time of the target vehicle to the data fusion module 220.

The radar may further report radar observation data, that is, radarmeasurement data, to the data fusion module 220. Herein, the radarmeasurement data includes feature information such as a location, aspeed, and a type of a target observed in a radar measurement scenario.Herein, the observed target may include roadside static obstacles thatare continuous and regular, a vehicle, and the like. This is not limitedin the embodiments of this application.

Correspondingly, the data fusion module 220 may receive, in real time,the camera measurement data reported by the camera and the radarmeasurement data reported by the radar. In some possibleimplementations, when receiving the travelling data of the targetvehicle reported by the camera, the data fusion module 220 may obtain afirst time period of travelling of the target vehicle, and then searchradar measurement data corresponding to the first time period forlocation information of the target vehicle, for example, coordinates[x_(r)(i),y_(r)(i)] of a position of the target vehicle, where irepresents time.

It should be noted that the foregoing location coordinates[x_(r)(i),y_(r)(i)] are coordinates of the first target in a localcoordinate system of the radar.

In addition, the first target is located in both sensing areas of thecamera and the radar, for example, the first target may be an object inthe area 103 in FIG. 2.

In some possible implementations, the data fusion module 220 mayalternatively search, based on the feature information provided by theradar such as the location, the speed, and the type of the observedtarget, the data reported by the camera for location informationcorresponding to the target.

420: Determine a calibration value of a radar sensor based on mapinformation and the first radar measurement data.

In some possible implementations, a fitting straight line track of thefirst target may be determined based on the foregoing first radarmeasurement data, and then a first slope of the fitting straight linetrack of the first target is determined. Then, a second slope of a roadreference target corresponding to the fitting straight line track of thefirst target may be determined based on the map information. In thiscase, the data fusion module 220 may determine the calibration value ofthe radar sensor based on the first slope and the second slope.

It should be noted that, in this embodiment of this application, thefirst slope is a slope of the fitting straight line track of the firsttarget in the local coordinate system of the radar, and the second slopeis a slope of the road reference target in a global coordinate system.In an example, when the map information is a GPS map, the globalcoordinate system may be a world coordinate system.

In an example, when the first radar measurement data representsinformation about a road edge (that is, a roadside line), a fittingstraight line track of the road edge may be determined, and a firstslope of the fitting straight line track is obtained. For example, whenthe first radar measurement data is coordinates [x_(r)(i),y_(r)(i)] of aplurality of stationary point targets, a linear regression equation maybe used to calculate a fitting straight line track of the plurality ofstationary points, and a first slope b_(r) of the fitting straight linetrack is calculated. For example, b_(r) may be shown in the followingformula (1):

$\begin{matrix}{b_{r} = \frac{{\Sigma_{i = 1}^{n}\left( {{x_{r}(i)} - \overset{\_}{x_{r}}} \right)}\left( {{y_{r}(i)} - \overset{\_}{y_{r}}} \right)}{\Sigma_{i = 1}^{n}\left( {{x_{r}(i)} - \overset{\_}{x_{r}}} \right)}} & (1)\end{matrix}$

Herein, n represents a quantity of sampling points, for example, may bea quantity of the plurality of stationary points. x _(r) and y _(r) areaverage numbers of x_(r)(i) and y_(r)(i) respectively.

Then, an included angle θ_(r) between the fitting straight line trackand the X_(R)-axis of the local coordinate system of the radar may bedetermined. In an example, θ_(r) may be represented as the followingformula (2):

θ_(r)=atan(b _(r))  (2)

Then, a road corresponding to the fitting straight line track of thefirst target may be searched for in the map information, and a secondslope of a reference target of the road is obtained. In an example inwhich the map information may be road information in the GPS map, afterthe road corresponding to the fitting straight line of the first targetis found in the GPS map, a plurality of coordinate points may beselected on a left lane line or a right lane line of the road, a fittingstraight line track corresponding to the plurality of coordinate pointsis obtained through fitting, and a second slope of the fitting straightline track is calculated.

For example, when position coordinates of the plurality of coordinatepoints are represented as [X_(l)(j),y_(l)(j)], the second slope b₁ ofthe fitting straight line track corresponding to the plurality ofcoordinate points may be represented as the following formula (3):

$\begin{matrix}{b_{l} = \frac{{\Sigma_{j = 1}^{m}\left( {{x_{l}(j)} - \overset{\_}{x_{l}}} \right)}\left( {{y_{l}(j)} - \overset{\_}{y_{l}}} \right)}{\Sigma_{j = 1}^{m}\left( {{x_{l}(j)} - \overset{\_}{x_{l}}} \right)}} & (3)\end{matrix}$

Herein, m represents a quantity of sampling points, for example, may bea quantity of the plurality of coordinate points. x _(l) and y _(l) areaverage numbers of x_(l)(i) and y_(l) (i) respectively.

Then, an included angle θ_(l) between the fitting straight line and theX_(G)-axis of the global coordinate system may be determined. In anexample, θ_(l) may be represented as the following formula (4):

θ_(l)=atan(b ₁)  (4)

Then, a calibration angle of the radar can be obtained by comparingθ_(r) with θ_(l). In an example, the calibration angle Δθ may berepresented as the following formula (5):

Δθ=θ_(l)−θ_(r)  (5)

It should be noted that the foregoing formula is an example used tofacilitate a person skilled in the art to understand the calibrationsolution of a sensor in the embodiments of this application, andconstitutes no limitation on the embodiments of this application. Forexample, the calibration angle Δθ may alternatively be θ_(r)−θ_(l). Foranother example, a person skilled in the art may alternatively obtain,in another manner or according to another formula, the fitting straightline track of the first target in the local coordinate system of theradar and the first slope, and/or the fitting straight line track of theroad reference target corresponding to the fitting straight line trackof the first target and the second slope. This is not limited in thisembodiment of this application.

It should be noted that when the first radar measurement data representsinformation about a road edge (that is, a roadside line), a roadsidestationary target position observed by using the radar is used as acalibration target. In this way, a sensing system does not haveexcessive requirements on a movement manner of a target obtained by thecamera, and is more applicable to a road scenario with a fence, such asa highway.

In another example, when the first radar measurement data representslocation information of the first target in the first time period, afitting straight line track of positions of the first target in thefirst time period may be determined, and a first slope of the fittingstraight line track is determined. Then, a road corresponding to thefitting straight line track of the first target may be searched for inthe map information, and a second slope of a reference target of theroad is determined. Then, the calibration angle of the radar isdetermined based on the first slope and the second slope. In someexamples, the fitting straight line track of the first target isparallel to a side line of the road corresponding to the fittingstraight line track of the first target, and therefore the first slopeand the second slope are the same.

In an example, in this case, the first target may be a moving object,such as a vehicle, and the location information of the first target inthe first time period is, for example, information such as locationcoordinates and a speed of the first target in the first time period.This is not limited in the embodiments of this application.

Specifically, for a process of determining the fitting straight linetrack of the positions of the first target in the first time period, anddetermining the first slope of the fitting straight line track, aprocess of determining the road corresponding to the fitting straightline track of the first target, and determining the second slope of thereference target of the road, and a process of determining thecalibration angle of the radar based on the first slope and the secondslope, refer to descriptions in the foregoing formulas (1) to (5). Forbrevity, details are not described herein again.

In another possible implementation, k first radar measurement valuescorresponding to k first targets may be obtained. Herein, the k firsttargets are corresponding to a same road reference target in the mapinformation, and k is an integer greater than or equal to 2. Then, kfitting straight line tracks corresponding to the k first targets aredetermined based on the k first radar measurement values correspondingto the k first targets, and an average value of k first slopescorresponding to the k fitting straight line tracks is determined. Then,a second slope of the first road reference target may be determinedbased on the map information. In this case, the data fusion module 220may determine the calibration value of the radar sensor based on theaverage value of the k first slopes and the second slope.

In an example, the foregoing k first targets are different targets atdifferent moments in a same lane.

Specifically, for a process of determining the first radar measurementvalue corresponding to each first target, refer to the description instep 410. For brevity, details are not described herein again. Inaddition, for a process of determining, based on each first radarmeasurement value, the fitting straight line track corresponding to eachfirst target, and determining the first slope of each fitting straightline track, refer to descriptions of the foregoing formula (1) andformula (2). For brevity, details are not described herein again.

For example, after the k first slopes corresponding to the k fittingstraight line tracks are determined, the average value {tilde over(θ)}_(r) of the k first slopes may be determined according to thefollowing formula (6):

$\begin{matrix}{{\overset{˜}{\theta}}_{r} = {\frac{1}{k}\Sigma_{i = 1}^{k}{\theta_{r}(i)}}} & (6)\end{matrix}$

Then, the calibration value of the radar sensor may be determined basedon the average value {tilde over (θ)}_(r) of the k first slopes and thesecond slope. Specifically, for a manner of determining the secondslope, refer to descriptions of the foregoing formula (4) and formula(5). For brevity, details are not described herein again.

In an example, the calibration angle Δθ of the radar sensor may berepresented as the following formula (7):

Δθ=θ_(l)−θ_(r)  (7)

It should be noted that the foregoing formula is an example used tofacilitate a person skilled in the art to understand the calibrationsolution of a sensor in the embodiments of this application, andconstitutes no limitation on the embodiments of this application. Forexample, the calibration angle Δθ may alternatively be θ_(r)−{tilde over(θ)}_(r).

Therefore, in this embodiment of this application, the average value ofthe plurality of first slopes is determined after location informationof the first target is measured for a plurality of times, and thecalibration value of the radar sensor is determined based on the averagevalue of the first slopes, thereby improving precision of thecalibration value of the radar sensor.

430: Determine first radar calibration measurement data of a secondtarget.

The first radar calibration measurement data is obtained based on secondradar measurement data of the second target and the calibration value ofthe radar sensor determined in step 420, and may be used to determinelocation information of the second target in the world coordinatesystem. In an example, the radar may obtain the second radar measurementdata of the second target, and then upload the second radar measurementdata to the data fusion module 220. The data fusion module 220determines radar calibration measurement data of the second target, thatis, the first radar calibration measurement data, based on the secondradar measurement data and the calibration value of the radar sensor.

In an example, the first radar calibration measurement data may be anAOA that is of the second target in the global coordinate system andobtained through calibration performed on an AOA measured by the radar.For example, when the AOA of the second target in the local coordinatesystem of the radar that is measured by the radar is {circumflex over(φ)}, the first radar calibration measurement data of the second targetmay be ({circumflex over (φ)}+Δθ).

In some possible implementations, for a second target that appears atdifferent moments in a same location in images obtained by the camera,location information that is of the second target appearing at thedifferent moments and observed by the radar may be further determined,and an average value of the plurality of pieces of location informationis determined. Then, first radar calibration measurement data of thesecond target is determined based on the average value of the pluralityof pieces of location information. Herein, the location information islocation information of the second target in the local coordinate systemof the radar. In an example, the location information may include, forexample, a distance and an AOA.

It should be noted that, because the plurality of second targets aretargets that appear at different moments in the same location obtainedby the camera, camera measurement data corresponding to the plurality ofsecond targets is the same.

Therefore, in this embodiment of this application, location informationof the second target is measured for a plurality of times, and theaverage value of the location information of the plurality of secondtargets is determined. Then, first radar calibration measurement data ofthe second targets is determined based on the average value of thelocation information of the plurality of second targets. This canimprove precision of radar calibration measurement data.

In a specific example, for h second targets that appear at h moments ina same location in images obtained by the camera, location informationof the h second targets that is observed by the radar may be obtained,where h is an integer greater than or equal to 2. Then, an average valueof the h pieces of location information may be determined. For example,the location information is a distance and an AOA. After the h pieces oflocation information of the h second targets in the local coordinatesystem of the radar are obtained, an average value d of distances a inthe h pieces of location information may be determined according to thefollowing formula (8):

$\begin{matrix}{\overset{˜}{d} = {\frac{1}{h}{\sum_{i = 1}^{h}{\overset{\hat{}}{d}(i)}}}} & (8)\end{matrix}$

An average value {tilde over (φ)} of AOAs {circumflex over (φ)} in the hpieces of location information may be determined according to thefollowing formula (9):

$\begin{matrix}{\overset{˜}{\varphi} = {\frac{1}{h}\Sigma_{i = 1}^{h}{\overset{\hat{}}{\varphi}(i)}}} & (9)\end{matrix}$

In this way, it may be determined that a first radar calibrationmeasurement value corresponding to the second target may be {tilde over(φ)}+Δθ.

440: Obtain first camera measurement data of the second target.

Herein, the camera may obtain camera measurement data of the secondtarget, that is, the first camera measurement data. Then, the camera maysend the first camera measurement data to the data fusion module 220.Correspondingly, the data fusion module 220 obtains the first camerameasurement data. Herein, the first camera measurement data is used toindicate location information of the second target in a local coordinatesystem of the camera.

In some possible implementations, the data fusion module 220 mayalternatively search, based on feature information such as a location, aspeed, and a type that are of the second target and that are provided bythe radar, data reported by the camera for the first camera measurementdata, that is, search for the location information of the second targetin the local coordinate system of the camera.

It should be noted that the second target needs to be located in boththe sensing areas of the camera and the radar, for example, may be anobject in the area 103 in FIG. 2.

In some possible implementations, the first target and the second targetmay be same objects, but implementation of this application is notlimited thereto.

450: Determine a calibration value of a camera sensor based on the firstradar calibration measurement data in step 430 and the first camerameasurement data in step 440.

In some possible embodiments, location information of the second targetin the world coordinate system may be determined based on the foregoingfirst radar calibration measurement data, and then the calibration valueof the camera sensor is determined based on the first camera measurementdata and the location information of the second target in the worldcoordinate system. In an example, calibration point coordinates in theglobal coordinate system that are corresponding to a pixel of the secondtarget in the local coordinate system of the camera are the locationinformation of the second target in the world coordinate system.

In a specific example, location information of the second target in theworld coordinate system at a moment w may be determined based onlocation information of the second target in the local coordinate systemof the radar at the moment w, which may be specifically shown in thefollowing formula (10):

$\begin{matrix}\left\{ \begin{matrix}{{\overset{\hat{}}{x}(w)} = {{{\overset{\hat{}}{d}(w)}*{\cos\left( {{\hat{\varphi}(w)} + {\Delta\theta}} \right)}} + x_{rad}}} \\{{\overset{\hat{}}{y}(w)} = {{{\overset{\hat{}}{d}(w)}*{\sin\left( {{\overset{\hat{}}{\varphi}(w)} + {\Delta\theta}} \right)}} + y_{rad}}}\end{matrix} \right. & (10)\end{matrix}$

Herein, {circumflex over (d)}(w) represents a distance between the radarand the second target observed by the radar at the moment w, {circumflexover (φ)}(w) represents an AOA of the second target in the localcoordinate system of the radar at the moment w, Δθ represents acalibration angle of the radar sensor, and [x_(rad),y_(rad)] representsa location of the radar in the global coordinate system.

For example, the pixel of the second target in the camera may berepresented as (u,v). In this case, the location information in theglobal coordinate system that is corresponding to the pixel (u,v) may be[{circumflex over (x)}(w),ŷ(w)].

In another specific example, location information of a plurality ofsecond targets in the world coordinate system may be determined based onan average value of a plurality of pieces of location information of theplurality of second targets in the local coordinate system of the radar,which may be specifically shown in the following formula (11):

$\begin{matrix}\left\{ \begin{matrix}{\overset{˜}{x} = {{\overset{˜}{d}*{\cos\left( {\overset{˜}{\varphi} + {\Delta\theta}} \right)}} + x_{rad}}} \\{\overset{˜}{y} = {{\overset{˜}{d}*{\sin\left( {\overset{˜}{\varphi} + {\Delta\theta}} \right)}} + y_{rad}}}\end{matrix} \right. & (11)\end{matrix}$

For example, a pixel of the second target in the camera may berepresented as (u,v). In this case, location information in the globalcoordinate system that is corresponding to the pixel (u,v) may be[{tilde over (x)},{tilde over (y)}].

In some possible implementations, a plurality of pieces of first radarcalibration measurement data corresponding to a second target thatappears at different moments in a same location in images obtained bythe camera may be further obtained. Then, a plurality of pieces oflocation information of the plurality of second targets in the worldcoordinate system may be determined based on the plurality of pieces offirst radar calibration measurement data, and an average value of theplurality of pieces of location information may be determined. Then, thecalibration value of the camera sensor may be determined based on theaverage value of the plurality of pieces of location information andfirst camera measurement data corresponding to the plurality of secondtargets.

In a specific example, for h second targets that appear at h moments ina same location in images obtained by the camera, after locationinformation of the h second targets that is observed by the radar isdetermined, first radar calibration measurement data of the h secondtargets may be determined. For example, the first radar calibrationmeasurement data of each second target may be represented as({circumflex over (φ)}(i)+Δθ).

Specifically, for a process of determining the first radar calibrationmeasurement value corresponding to each second target, refer to thedescription in step 430. For brevity, details are not described hereinagain.

Then, h pieces of location information of the h second targets in theworld coordinate system may be determined based on the h pieces of firstradar calibration measurement data of the h second targets. In anexample, the h pieces of location information may be represented as thefollowing formula (12):

$\begin{matrix}\left\{ \begin{matrix}{{\overset{\hat{}}{x}(i)} = {{{\overset{\hat{}}{d}(i)}*{\cos\left( {{\overset{\hat{}}{\varphi}(i)} + {\Delta\theta}} \right)}} + x_{rad}}} \\{{\overset{\hat{}}{y}(i)} = {{{\overset{\hat{}}{d}(i)}*{\sin\left( {{\overset{\hat{}}{\varphi}(i)} + {\Delta\theta}} \right)}} + y_{rad}}}\end{matrix} \right. & (12)\end{matrix}$

Herein, a value of i may be 1, . . . , h.

An average value of the h pieces of location information of the h secondtargets may be represented as the following formula (13):

$\begin{matrix}\left\{ \begin{matrix}{\overset{˜}{x} = {\frac{1}{h}\Sigma_{i = 1}^{h}{\overset{\hat{}}{x}\ (i)}}} \\{\overset{˜}{y} = {\frac{1}{h}\Sigma_{i = 1}^{h}{\overset{\hat{}}{y}\ (i)}}}\end{matrix} \right. & (13)\end{matrix}$

For example, a pixel of the second target in the camera may berepresented as (u,v). In this case, location information in the globalcoordinate system that is corresponding to the pixel (u,v) may be[{tilde over (x)},{tilde over (y)}].

Therefore, in this embodiment of this application, location informationof the second target is measured for a plurality of times, a pluralityof pieces of location information in the world coordinate system thatare corresponding to the location information of the plurality of secondtargets are determined, and then an average value of the plurality ofpieces of location information of the plurality of second targets in theworld coordinate system is determined. Then, the calibration value ofthe camera sensor is determined based on the average value. This canimprove precision of the calibration value of the camera sensor.

In some possible implementations of this application, locationinformation of at least one pixel of the second target in the globalcoordinate system may be obtained in the foregoing manner, and then aconversion relationship between a location of a target in the localcoordinate system of the camera 120 and a location of the target in theglobal coordinate system, that is, the calibration parameter of thecamera, may be determined based on location information of the at leastone pixel in the local coordinate system of the camera and the locationinformation of the at least one pixel in the global coordinate system.In an example, the conversion relationship may be determined based onlocation information of nine pixels of the second target in the localcoordinate system of the camera and location information of the ninepixels in the global coordinate system. However, the embodiments of thisapplication are not limited thereto.

Therefore, in this embodiment of this application, location informationof a target detected by the radar is matched against the map informationto determine the calibration value of the radar sensor, and thenlocation information of a pixel of a target corresponding to the camerain the global coordinate system may be determined based on calibratedradar measurement data, that is, radar calibration measurement data, soas to further determine the calibration value of the camera sensor.Therefore, according to the sensor space calibration solution providedin the embodiment of this application, for a sensing system thatincludes a single radar and a monocular camera, manual field calibrationis no longer required, which can effectively improve calibrationefficiency of sensors in the sensing system.

FIG. 5 is a schematic flowchart of another sensor calibration method 500according to an embodiment of this application. In an example, themethod includes steps 510 and 520.

510: A fusion processing module sends a calibration value of a sensor ofa camera to the camera. Correspondingly, the camera receives thecalibration value of the camera sensor that is sent by the fusionprocessing module. The calibration value of the camera sensor isobtained based on first radar calibration measurement data of a secondtarget and first camera measurement data of the second target, and thefirst radar calibration measurement data is obtained based on secondradar measurement data of the second target and a calibration value ofthe radar sensor.

Specifically, for a process of determining the calibration value of thecamera sensor, refer to the foregoing description in FIG. 4. Forbrevity, details are not described herein again.

520: The camera calibrates a measurement parameter of the camera sensorbased on the calibration value of the camera sensor.

Specifically, the camera may convert the measurement parameter of thecamera sensor from a local coordinate system of the camera to a globalcoordinate system based on the calibration value of the camera sensor.

Therefore, in this embodiment of this application, the camera mayreceive the calibration value of the camera sensor sent by the fusionprocessing module, and then may calibrate the measurement parameter ofthe camera sensor based on the calibration value of the camera sensor.Therefore, according to the sensor space calibration solution providedin the embodiment of this application, for a sensing system thatincludes a single radar and a monocular camera, manual field calibrationis no longer required, which can effectively improve calibrationefficiency of sensors in the sensing system.

In some possible implementations, the camera may further obtain camerameasurement data of a plurality of targets, then determine, based on thecamera measurement data of the plurality of targets, a first target thatmeets a preset reporting condition in the plurality of targets, andobtain travelling data of the first target. Then, the camera sends thetravelling data of the first target to the fusion processing module. Thetravelling data is used to indicate the fusion module to search radarmeasurement data collected by the radar sensor for first radarmeasurement data that is of the first target and matches the travellingdata.

In an example, the preset reporting condition is that vehicles in ascene picture photographed by the camera are sparse, for example, onlyone vehicle exists. In this case, the vehicle may be used as the firsttarget. For details, refer to the description of 410 in FIG. 4. Forbrevity, details are not described herein again.

FIG. 6 is a schematic flowchart of another sensor calibration method 600according to an embodiment of this application. In an example, themethod includes steps 610 and 620.

610: Receive a calibration value of a radar sensor sent by a fusionprocessing module, where the calibration value of the radar sensor isobtained based on first radar measurement data of a first target and mapdata.

620: Calibrate a measurement parameter of the radar sensor based on thecalibration value of the radar sensor.

Therefore, in this embodiment of this application, the radar may receivethe calibration value of the radar sensor sent by the fusion processingmodule, and then may calibrate the measurement parameter of the radarsensor based on the calibration value of the radar sensor. Therefore,according to the sensor space calibration solution provided in theembodiment of this application, for a sensing system that includes asingle radar and a monocular camera, manual field calibration is nolonger required, which can effectively improve calibration efficiency ofsensors in the sensing system.

FIG. 7 is a schematic block diagram of a sensor calibration apparatus700 according to an embodiment of this application. In an example, theapparatus 700 may be the foregoing fusion processing module. Theapparatus 700 includes an obtaining unit 710 and a determining unit 720.

The obtaining unit 710 is configured to obtain first radar measurementdata of a first target.

The determining unit 720 is configured to determine a calibration valueof a radar sensor based on map information and the first radarmeasurement data.

The determining unit 720 is further configured to determine first radarcalibration measurement data of a second target, where the first radarcalibration measurement data is obtained based on second radarmeasurement data of the second target and the calibration value of theradar sensor.

The obtaining unit 710 is further configured to obtain first camerameasurement data of the second target.

The determining unit 720 is further configured to determine acalibration value of a camera sensor based on the first radarcalibration measurement data and the first camera measurement data.

In some possible implementations, the determining unit 720 isspecifically configured to: determine a fitting straight line track ofthe first target based on the first radar measurement data; determine afirst slope of the fitting straight line track of the first target;determine, based on the map information, a second slope of a first roadreference target in a world coordinate system, where the first roadreference target is corresponding to the fitting straight line track ofthe first target; and determine the calibration value of the radarsensor based on the first slope and the second slope.

In some possible implementations, the determining unit 720 isspecifically configured to: obtain k first radar measurement valuescorresponding to k first targets, where the k first targets arecorresponding to a first road reference target in the map information,and k is an integer greater than or equal to 2; determine, based on nfirst radar measurement values corresponding to the k first targets, kfitting straight line tracks corresponding to the k first targets;determine an average value of k first slopes corresponding to the kfitting straight line tracks; determine a second slope of the first roadreference target in a world coordinate system based on the mapinformation; and determine the calibration value of the radar sensorbased on the average value of the k first slopes and the second slope.

In some possible implementations, the determining unit 720 isspecifically configured to: determine location information of the secondtarget in the world coordinate system based on the first radarcalibration measurement data; and determine the calibration value of thecamera sensor based on the first camera measurement data and thelocation information of the second target in the world coordinatesystem.

In some possible implementations, the determining unit 720 isspecifically configured to: obtain h pieces of first radar calibrationmeasurement data corresponding to h second targets and h pieces of firstcamera measurement data of the h second targets, where the first camerameasurement data of the h second targets is the same, and h is aninteger greater than or equal to 2; determine h pieces of locationinformation of the h second targets in the world coordinate system basedon the h pieces of first radar calibration measurement data of the hsecond targets; determine an average value of the h pieces of locationinformation of the h second targets; and determine the calibration valueof the camera sensor based on the average value of the h pieces oflocation information of the h second targets and the h pieces of firstcamera measurement data of the h second targets.

In some possible implementations, the obtaining unit 710 is specificallyconfigured to: obtain travelling data of the first target collected bythe camera sensor; and search radar measurement data collected by theradar sensor for the first radar measurement data that matches thetravelling data.

In some possible implementations, the apparatus 700 may further includea sending unit, configured to send the determined calibration value ofthe radar sensor to the radar, and send the calibration value of thecamera sensor to the camera.

Therefore, in this embodiment of this application, location informationof a target detected by the radar is matched against the map informationto determine the calibration value of the radar sensor, and thenlocation information of a pixel of a target corresponding to the camerain the global coordinate system may be determined based on calibratedradar measurement data, that is, radar calibration measurement data, soas to further determine the calibration value of the camera sensor.Therefore, according to the sensor space calibration solution providedin the embodiment of this application, for a sensing system thatincludes a single radar and a monocular camera, manual field calibrationis no longer required, which can effectively improve calibrationefficiency of sensors in the sensing system.

It should be noted that in this embodiment of the present invention, theobtaining unit 710 may be implemented by a receiver, and the determiningunit 720 may be implemented by a processor.

The sensor calibration apparatus 700 shown in FIG. 7 can implementprocesses corresponding to the foregoing method embodiment shown in FIG.4. Specifically, for the sensor calibration apparatus 700, refer to theforegoing description in FIG. 4. To avoid repetition, details are notdescribed herein again.

FIG. 8 is a schematic block diagram of another sensor calibrationapparatus 800 according to an embodiment of this application. In anexample, the apparatus 800 may be the foregoing camera. The apparatus800 includes a receiving unit 810 and a processing unit 820.

The receiving unit 810 is configured to receive a calibration value of acamera sensor sent by a fusion processing module, where the calibrationvalue of the camera sensor is obtained based on first radar calibrationmeasurement data of a second target and first camera measurement data ofthe second target, and the first radar calibration measurement data isobtained based on second radar measurement data of the second target anda calibration value of the radar sensor.

The processing unit 820 is configured to calibrate the measurementparameter of the camera sensor based on the calibration value of thecamera sensor.

In some possible implementations, the apparatus 800 further includes: anobtaining unit, configured to obtain camera measurement data of aplurality of targets, where the processing unit 820 is furtherconfigured to determine, from the plurality of targets based on thecamera measurement data of the plurality of targets that is obtained bythe obtaining unit, a first target that meets a preset reportingcondition, and the obtaining unit is further configured to obtaintravelling data of the first target; and a sending unit, configured tosend the travelling data of the first target to the fusion processingmodule, where the travelling data is used to indicate the fusion moduleto search radar measurement data collected by the radar sensor for firstradar measurement data that is of the first target and matches thetravelling data.

Therefore, in this embodiment of this application, the camera mayreceive the calibration value of the camera sensor sent by the fusionprocessing module, and then may calibrate the measurement parameter ofthe camera sensor based on the calibration value of the camera sensor.Therefore, according to the sensor space calibration solution providedin the embodiment of this application, for a sensing system thatincludes a single radar and a monocular camera, manual field calibrationis no longer required, which can effectively improve calibrationefficiency of sensors in the sensing system.

It should be noted that in this embodiment of the present invention, thereceiving unit 810 may be implemented by a receiver, and the processingunit 820 may be implemented by a processor.

The sensor calibration apparatus 800 shown in FIG. 8 can implementprocesses corresponding to the foregoing method embodiment shown in FIG.5. Specifically, for the sensor calibration apparatus 800, refer to theforegoing description in FIG. 5. To avoid repetition, details are notdescribed herein again.

FIG. 9 is a schematic block diagram of a sensor calibration apparatus900 according to an embodiment of this application. In an example, theapparatus 900 may be the foregoing radar. The apparatus 900 includes areceiving unit 910 and a processing unit 920.

The receiving unit 910 is configured to receive a calibration value of aradar sensor sent by a fusion processing module, where the calibrationvalue of the radar sensor is obtained based on first radar measurementdata of a first target and map data.

The processing unit 920 is configured to calibrate a measurementparameter of the radar sensor based on the calibration value of theradar sensor.

Therefore, in this embodiment of this application, the radar may receivethe calibration value of the radar sensor sent by the fusion processingmodule, and then may calibrate the measurement parameter of the radarsensor based on the calibration value of the radar sensor. Therefore,according to the sensor space calibration solution provided in theembodiment of this application, for a sensing system that includes asingle radar and a monocular camera, manual field calibration is nolonger required, which can effectively improve calibration efficiency ofsensors in the sensing system.

FIG. 10 is a schematic block diagram of a sensor calibration apparatus1000 according to an embodiment of this application. In an example, theapparatus 1000 may be a fusion processing module, a camera, or a radar.As shown in FIG. 10, the apparatus 1000 may include a processor 1010 anda transceiver 1030. Optionally, the apparatus 1000 may further include amemory 1020.

The memory 1020 may be configured to store instructions or code used bythe processor 1010 to execute the sensor calibration method, or acalibration parameter for calibrating the sensor, or intermediate dataused in a process of determining the calibration parameter. Theprocessor 1010 may be configured to execute the instructions stored inthe memory 1020, to enable the apparatus 1000 to implement stepsperformed by the fusion processing module, the camera, or the radar inthe foregoing method. Alternatively, the processor 1010 may beconfigured to invoke data of the memory 1020, to enable the apparatus1000 to implement steps performed by the fusion processing module, thecamera, or the radar in the foregoing method.

For example, the processor 1010, the memory 1020, and the transceiver1030 may use an internal connection channel to communicate with eachother, and transmit control and/or data signals. For example, the memory1020 is configured to store a computer program, and the processor 1010may be configured to invoke and run the computer program from the memory1020, to control the transceiver 1030 to receive a signal and/or send asignal, so as to complete steps corresponding to the foregoing method.The memory 1020 may be integrated into the processor 1010, or may beseparated from the processor 1010.

In an implementation, it may be considered that a function of thetransceiver 1030 is implemented by using a transceiver circuit or aspecial-purpose transceiver chip. It may be considered that theprocessor 1010 is implemented by using a dedicated processing chip, aprocessing circuit, a processing unit, or a general-purpose chip.

In another implementation, a general-purpose computer may be used toimplement the sensor calibration apparatus provided in the embodiment ofthis application. That is, program code for implementing functions ofthe processor 1010 and the transceiver 1030 is stored in the memory1020. A general-purpose processing unit implements functions of theprocessor 1010 and the transceiver 1030 by executing the code in thememory 1020.

For example, when the apparatus 1000 is configured in a fusionprocessing module or is a fusion processing module, modules or units inthe apparatus 1000 may be configured to execute actions or processingprocesses executed by the fusion processing module in the foregoingmethod. To avoid repeated description herein, detailed descriptionthereof is omitted.

For example, when the apparatus 1000 is configured in a camera or is acamera, modules or units in the apparatus 1000 may be configured toexecute actions or processing processes executed by the camera in theforegoing method. To avoid repeated description herein, detaileddescription thereof is omitted.

For example, when the apparatus 1000 is configured in a radar or is aradar, modules or units in the apparatus 1000 may be configured toexecute actions or processing processes executed by the radar in theforegoing method. To avoid repeated description herein, detaileddescription thereof is omitted.

For concepts, explanations, detailed descriptions, and other steps ofthe apparatus 1000 that are related to the technical solutions providedin the embodiments of this application, refer to the descriptions of thecontent in the foregoing methods or other embodiments. Details are notdescribed herein again.

It should be understood that, the processor mentioned in the embodimentsof the present invention may be a central processing unit (centralprocessing unit, CPU), or may be another general-purpose processor, adigital signal processor (digital signal processor, DSP), an applicationspecific integrated circuit (application specific integrated circuit,ASIC), a field programmable gate array (field programmable gate array,FPGA) or another programmable logic device, a discrete gate or atransistor logic device, a discrete hardware component, or the like. Thegeneral-purpose processor may be a microprocessor, or the processor maybe any conventional processor, or the like.

It should be further understood that, the memory mentioned in theembodiments of the present invention may be a volatile memory or anonvolatile memory, or may include a volatile memory and a nonvolatilememory. The nonvolatile memory may be a read-only memory (read-onlymemory, ROM), a programmable read-only memory (programmable ROM, PROM),an erasable programmable read-only memory (erasable PROM, EPROM), anelectrically erasable programmable read-only memory (electrically EPROM,EEPROM), or a flash memory. The volatile memory may be a random accessmemory (random access memory, RAM) that is used as an external cache. Byway of example but not limitative description, many forms of RAMs may beused, for example, a static random access memory (static RAM, SRAM), adynamic random access memory (dynamic RAM, DRAM), a synchronous dynamicrandom access memory (synchronous DRAM, SDRAM), a double data ratesynchronous dynamic random access memory (double data rate SDRAM, DDRSDRAM), an enhanced synchronous dynamic random access memory (enhancedSDRAM, ESDRAM), a synchlink dynamic random access memory (synchlinkDRAM, SLDRAM), and a direct rambus random access memory (direct rambusRAM, DR RAM).

It should be noted that, when the processor is a general-purposeprocessor, a DSP, an ASIC, an FPGA or another programmable logic device,a discrete gate or a transistor logic device, or a discrete hardwarecomponent, the memory (a storage module) is integrated into theprocessor.

It should be noted that, the memory described in this specification isintended to include but is not limited to these memories and any otherappropriate types of memories.

An embodiment of this application further provides a computer-readablestorage medium. The computer-readable storage medium includes a computerprogram. When the computer program is run on a computer, the computer isenabled to perform the methods provided in the foregoing methodembodiments.

An embodiment of this application further provides a computer programproduct including instructions. When the computer program product runson a computer, the computer is enabled to perform the methods providedin the foregoing method embodiments.

An embodiment of this application further provides a chip, including aprocessor and a communications interface. The processor is configured toinvoke and run instructions from the communications interface. When theprocessor executes the instructions, the method provided in theforegoing method embodiment is implemented.

It should be understood that sequence numbers of the foregoing processesdo not mean execution sequences in the embodiments of this application.The execution sequences of the processes should be determined based onfunctions and internal logic of the processes, and should not beconstrued as any limitation on implementation processes of theembodiments of this application.

It should be understood that the descriptions of “first”, “second”, andthe like in the embodiments of this application are merely used toillustrate and distinguish description objects, and there is nosequence. The descriptions of “first”, “second”, and the like do notrepresent a special limitation on a quantity of devices in theembodiments of this application, and cannot constitute any limitation onthe embodiments of this application.

A person of ordinary skill in the art may be aware that, in combinationwith the examples described in the embodiments disclosed in thisspecification, units and algorithm steps may be implemented byelectronic hardware or a combination of computer software and electronichardware. Whether the functions are performed by the hardware or thesoftware depends on particular applications and design constraints ofthe technical solutions. A person skilled in the art may use differentmethods to implement the described functions for each particularapplication, but it should not be considered that the implementationgoes beyond the scope of this application.

It may be clearly understood by a person skilled in the art that for thepurpose of convenient and brief description, for a detailed workingprocess of the described systems, apparatuses, and units, refer to acorresponding process in the foregoing method embodiments. Details arenot described herein again.

In the several embodiments provided in this application, it should beunderstood that the disclosed system, apparatus, and method may beimplemented in other manners. For example, the described apparatusembodiments are merely examples. For example, division into the units ismerely logical function division and may be other division during actualimplementation. For example, a plurality of units or components may becombined or integrated into another system, or some features may beignored or not performed. In addition, the displayed or discussed mutualcoupling or direct coupling or communication connections may beimplemented by using some interfaces. The indirect coupling orcommunication connections between the apparatuses or units may beimplemented in electrical, mechanical, or other forms.

The units described as separate parts may or may not be physicallyseparate, and parts displayed as units may or may not be physical units,may be located at one position, or may be distributed on a plurality ofnetwork units. Some or all of the units may be selected based on actualrequirements to achieve the objectives of the solutions of theembodiments.

In addition, functional units in the embodiments of this application maybe integrated into one processing unit, each of the units may existalone physically, or two or more units are integrated into one unit.

When the functions are implemented in the form of a software functionalunit and sold or used as an independent product, the functions may bestored in a computer-readable storage medium. Based on such anunderstanding, the technical solutions of this application essentially,or the part contributing to the prior art, or some of the technicalsolutions may be implemented in a form of a software product. Thecomputer software product is stored in a storage medium, and includesseveral instructions for instructing a computer device (which may be apersonal computer, a server, a network device, or the like) to performall or some of the steps of the methods in the embodiments of thisapplication. The foregoing storage medium includes any medium that canstore program code, for example, a USB flash drive, a removable harddisk, a read-only memory (read-only memory, ROM), a random access memory(random access memory, RAM), a magnetic disk, or an optical disc.

The foregoing descriptions are merely specific implementations of thisapplication, but are not intended to limit the protection scope of thisapplication. Any variation or replacement readily figured out by aperson skilled in the art within the technical scope disclosed in thisapplication shall fall within the protection scope of this application.Therefore, the protection scope of this application shall be subject tothe protection scope of the claims.

What is claimed is:
 1. A sensor calibration method, comprising:obtaining first radar measurement data of a first target; determining acalibration value of a radar sensor based on map information and thefirst radar measurement data; determining first radar calibrationmeasurement data of a second target, wherein the first radar calibrationmeasurement data is obtained based on second radar measurement data ofthe second target and the calibration value of the radar sensor;obtaining first camera measurement data of the second target; anddetermining a calibration value of a camera sensor based on the firstradar calibration measurement data and the first camera measurementdata.
 2. The method according to claim 1, wherein the determining acalibration value of a radar sensor based on map information and thefirst radar measurement data comprises: determining a fitting straightline track of the first target based on the first radar measurementdata; determining a first slope of the fitting straight line track ofthe first target; determining, based on the map information, a secondslope of a first road reference target in a world coordinate system,wherein the first road reference target is corresponding to the fittingstraight line track of the first target; and determining the calibrationvalue of the radar sensor based on the first slope and the second slope.3. The method according to claim 1, wherein the determining acalibration value of a radar sensor based on map information and thefirst radar measurement data comprises: obtaining n first radarmeasurement values corresponding to k first targets, wherein the k firsttargets are corresponding to a first road reference target in the mapinformation, and k is an integer greater than or equal to 2;determining, based on the n first radar measurement values correspondingto the k first targets, k fitting straight line tracks corresponding tothe k first targets; determining an average value of k first slopescorresponding to the k fitting straight line tracks; determining asecond slope of the first road reference target in a world coordinatesystem based on the map information; and determining the calibrationvalue of the radar sensor based on the average value of the k firstslopes and the second slope.
 4. The method according to claim 1, whereinthe determining a calibration value of a camera sensor based on thefirst radar calibration measurement data and the first camerameasurement data comprises: determining location information of thesecond target in the world coordinate system based on the first radarcalibration measurement data; and determining the calibration value ofthe camera sensor based on the first camera measurement data and thelocation information of the second target in the world coordinatesystem.
 5. The method according to claim 2, wherein the determining acalibration value of a camera sensor based on the first radarcalibration measurement data and the first camera measurement datacomprises: determining location information of the second target in theworld coordinate system based on the first radar calibration measurementdata; and determining the calibration value of the camera sensor basedon the first camera measurement data and the location information of thesecond target in the world coordinate system.
 6. The method according toclaim 3, wherein the determining a calibration value of a camera sensorbased on the first radar calibration measurement data and the firstcamera measurement data comprises: determining location information ofthe second target in the world coordinate system based on the firstradar calibration measurement data; and determining the calibrationvalue of the camera sensor based on the first camera measurement dataand the location information of the second target in the worldcoordinate system.
 7. The method according to claim 1, wherein thedetermining a calibration value of a camera sensor based on the firstradar calibration measurement data and the first camera measurement datacomprises: obtaining h pieces of first radar calibration measurementdata corresponding to h second targets and h pieces of first camerameasurement data of the h second targets, wherein the first camerameasurement data of the h second targets is the same, and h is aninteger greater than or equal to 2; determining h pieces of locationinformation of the h second targets in the world coordinate system basedon the h pieces of first radar calibration measurement data of the hsecond targets; determining an average value of the h pieces of locationinformation of the h second targets; and determining the calibrationvalue of the camera sensor based on the average value of the h pieces oflocation information of the h second targets and the h pieces of firstcamera measurement data of the h second targets.
 8. The method accordingto claim 2, wherein the determining a calibration value of a camerasensor based on the first radar calibration measurement data and thefirst camera measurement data comprises: obtaining h pieces of firstradar calibration measurement data corresponding to h second targets andh pieces of first camera measurement data of the h second targets,wherein the first camera measurement data of the h second targets is thesame, and h is an integer greater than or equal to 2; determining hpieces of location information of the h second targets in the worldcoordinate system based on the h pieces of first radar calibrationmeasurement data of the h second targets; determining an average valueof the h pieces of location information of the h second targets; anddetermining the calibration value of the camera sensor based on theaverage value of the h pieces of location information of the h secondtargets and the h pieces of first camera measurement data of the hsecond targets.
 9. The method according to claim 1, wherein theobtaining first radar measurement data of a first target comprises:obtaining travelling data of the first target collected by the camerasensor; and searching radar measurement data collected by the radarsensor for the first radar measurement data that matches the travellingdata.
 10. A sensor calibration apparatus, comprising: a memoryconfigured to store instructions; and one or more processors coupled tothe memory and configured to execute the instructions to cause theapparatus to: obtain first radar measurement data of a first target;determine a calibration value of a radar sensor based on map informationand the first radar measurement data; determine first radar calibrationmeasurement data of a second target, wherein the first radar calibrationmeasurement data is obtained based on second radar measurement data ofthe second target and the calibration value of the radar sensor; obtainfirst camera measurement data of the second target; and determine acalibration value of a camera sensor based on the first radarcalibration measurement data and the first camera measurement data. 11.The apparatus according to claim 10, wherein the determine a calibrationvalue of a radar sensor based on map information and the first radarmeasurement data comprises: determining a fitting straight line track ofthe first target based on the first radar measurement data; determininga first slope of the fitting straight line track of the first target;determining, based on the map information, a second slope of a firstroad reference target in a world coordinate system, wherein the firstroad reference target is corresponding to the fitting straight linetrack of the first target; and determining the calibration value of theradar sensor based on the first slope and the second slope.
 12. Theapparatus according to claim 10, wherein the determine a calibrationvalue of a radar sensor based on map information and the first radarmeasurement data comprises: obtain n first radar measurement valuescorresponding to k first targets, wherein the k first targets arecorresponding to a first road reference target in the map information,and k is an integer greater than or equal to 2; determine, based on then first radar measurement values corresponding to the k first targets, kfitting straight line tracks corresponding to the k first targets;determine an average value of k first slopes corresponding to the kfitting straight line tracks; determine a second slope of the first roadreference target in a world coordinate system based on the mapinformation; and determine the calibration value of the radar sensorbased on the average value of the k first slopes and the second slope.13. The apparatus according to claim 10, wherein the determine acalibration value of a camera sensor based on the first radarcalibration measurement data and the first camera measurement datacomprises: determine location information of the second target in theworld coordinate system based on the first radar calibration measurementdata; and determine the calibration value of the camera sensor based onthe first camera measurement data and the location information of thesecond target in the world coordinate system.
 14. The apparatusaccording to claim 11, wherein the determine a calibration value of acamera sensor based on the first radar calibration measurement data andthe first camera measurement data comprises: determine locationinformation of the second target in the world coordinate system based onthe first radar calibration measurement data; and determine thecalibration value of the camera sensor based on the first camerameasurement data and the location information of the second target inthe world coordinate system.
 15. The apparatus according to claim 12,wherein the determine a calibration value of a camera sensor based onthe first radar calibration measurement data and the first camerameasurement data comprises: determine location information of the secondtarget in the world coordinate system based on the first radarcalibration measurement data; and determine the calibration value of thecamera sensor based on the first camera measurement data and thelocation information of the second target in the world coordinatesystem.
 16. The apparatus according to claim 10, wherein the determine acalibration value of a camera sensor based on the first radarcalibration measurement data and the first camera measurement datacomprises: obtain h pieces of first radar calibration measurement datacorresponding to h second targets and h pieces of first camerameasurement data of the h second targets, wherein the first camerameasurement data of the h second targets is the same, and h is aninteger greater than or equal to 2; determine h pieces of locationinformation of the h second targets in the world coordinate system basedon the h pieces of first radar calibration measurement data of the hsecond targets; determine an average value of the h pieces of locationinformation of the h second targets; and determine the calibration valueof the camera sensor based on the average value of the h pieces oflocation information of the h second targets and the h pieces of firstcamera measurement data of the h second targets.
 17. The apparatusaccording to claim 11, wherein the determine a calibration value of acamera sensor based on the first radar calibration measurement data andthe first camera measurement data comprises: obtain h pieces of firstradar calibration measurement data corresponding to h second targets andh pieces of first camera measurement data of the h second targets,wherein the first camera measurement data of the h second targets is thesame, and h is an integer greater than or equal to 2; determine h piecesof location information of the h second targets in the world coordinatesystem based on the h pieces of first radar calibration measurement dataof the h second targets; determine an average value of the h pieces oflocation information of the h second targets; and determine thecalibration value of the camera sensor based on the average value of theh pieces of location information of the h second targets and the hpieces of first camera measurement data of the h second targets.
 18. Themethod according to claim 10, wherein the obtain first radar measurementdata of a first target comprises: obtain travelling data of the firsttarget collected by the camera sensor; and search radar measurement datacollected by the radar sensor for the first radar measurement data thatmatches the travelling data.
 19. A sensor calibration apparatus,comprising: a memory configured to store instructions; and one or moreprocessors coupled to the memory and configured to execute theinstructions to cause the apparatus to: receive a calibration value of acamera sensor sent by a fusion processing module, wherein thecalibration value of the camera sensor is obtained based on first radarcalibration measurement data of a second target and first camerameasurement data of the second target, and the first radar calibrationmeasurement data is obtained based on second radar measurement data ofthe second target and a calibration value of the radar sensor; andcalibrate a measurement parameter of the camera sensor based on thecalibration value of the camera sensor.
 20. The apparatus according toclaim 19, wherein the instructions further cause the apparatus to:obtain camera measurement data of a plurality of targets; determine,from the plurality of targets based on the camera measurement data, afirst target that meets a preset reporting condition; obtain travellingdata of the first target; and send the travelling data of the firsttarget to the fusion processing module, wherein the travelling data isused to indicate the fusion module to search radar measurement datacollected by the radar sensor for first radar measurement data that isof the first target and matches the travelling data.